Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/51905
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dc.contributor.authorTohidi, Faranaken
dc.contributor.authorPaul, Manoranjanen
dc.contributor.authorHooshmandasl, Mohammad Rezaen
dc.contributor.authorChakraborty, Subrataen
dc.contributor.authorPradhan, Biswajeeten
local.source.editorEditor(s): Joel Janek Dabrowski, Ashfaqur Rahman and Manoranjan Paulen
dc.date.accessioned2022-05-03T03:50:12Z-
dc.date.available2022-05-03T03:50:12Z-
dc.date.issued2020-
dc.identifier.citationImage and Video Technology: PSIVT 2019, p. 86-99en
dc.identifier.isbn9783030397708en
dc.identifier.isbn9783030397692en
dc.identifier.urihttps://hdl.handle.net/1959.11/51905-
dc.description.abstract<p>Digital images are used to transfer most critical data in areas like medical, research, business, military, etc. The images transfer takes place over an unsecured Internet network. Therefore, there is a need for reliable security and protection for these sensitive images. Medical images play an important role in the field of Telemedicine and Tele surgery. Thus, before making any diagnostic decisions and treatments, the authenticity and the integrity of the received medical images need to be verified to avoid misdiagnosis. This paper proposes a block-wise and blind fragile watermarking mechanism for medical image authentication and recovery. By eliminating embedded insignificant data and considering different content complexity for each block during feature extraction and recovery, the capacity of data embedding without loss of quality is increased. This new embedding watermark method can embed a copy of the compressed image inside itself as a watermark to increase the recovered image quality. In our proposed hybrid scheme, the block features are utilized to improve the efficiency of data concealing for authentication and reduce tampering. Therefore, the scheme can achieve better results in terms of the recovered image quality and greater tampering protection, compared with the current schemes.</p>en
dc.languageenen
dc.publisherSpringeren
dc.relation.ispartofImage and Video Technology: PSIVT 2019en
dc.relation.ispartofseriesLecture Notes in Computer Scienceen
dc.titleBlock-Wise Authentication and Recovery Scheme for Medical Images Focusing on Content Complexityen
dc.typeConference Publicationen
dc.relation.conferencePSIVT 2019: 9th Pacific-Rim Symposium on Image and Video Technology Workshopsen
dc.identifier.doi10.1007/978-3-030-39770-8_7en
local.contributor.firstnameFaranaken
local.contributor.firstnameManoranjanen
local.contributor.firstnameMohammad Rezaen
local.contributor.firstnameSubrataen
local.contributor.firstnameBiswajeeten
local.profile.schoolSchool of Science and Technologyen
local.profile.emailschakra3@une.edu.auen
local.output.categoryE1en
local.record.placeauen
local.record.institutionUniversity of New Englanden
local.date.conference18th - 22nd November, 2019en
local.conference.placeSydney, Australiaen
local.publisher.placeCham, Switzerlanden
local.format.startpage86en
local.format.endpage99en
local.identifier.scopusid85080866893en
local.series.issn1611-3349en
local.series.issn0302-9743en
local.series.number11994en
local.peerreviewedYesen
local.contributor.lastnameTohidien
local.contributor.lastnamePaulen
local.contributor.lastnameHooshmandaslen
local.contributor.lastnameChakrabortyen
local.contributor.lastnamePradhanen
local.seriespublisherSpringeren
local.seriespublisher.placeCham, Switzerlanden
dc.identifier.staffune-id:schakra3en
local.profile.orcid0000-0002-0102-5424en
local.profile.roleauthoren
local.profile.roleauthoren
local.profile.roleauthoren
local.profile.roleauthoren
local.profile.roleauthoren
local.identifier.unepublicationidune:1959.11/51905en
local.date.onlineversion2020-01-27-
dc.identifier.academiclevelAcademicen
dc.identifier.academiclevelAcademicen
dc.identifier.academiclevelAcademicen
dc.identifier.academiclevelAcademicen
dc.identifier.academiclevelAcademicen
local.title.maintitleBlock-Wise Authentication and Recovery Scheme for Medical Images Focusing on Content Complexityen
local.output.categorydescriptionE1 Refereed Scholarly Conference Publicationen
local.relation.urlhttp://www.psivt.org/psivt2019/program.htmlen
local.conference.detailsPSIVT 2019: 9th Pacific-Rim Symposium on Image and Video Technology Workshops, Sydney, Australia, 18th - 22nd November, 2019en
local.search.authorTohidi, Faranaken
local.search.authorPaul, Manoranjanen
local.search.authorHooshmandasl, Mohammad Rezaen
local.search.authorChakraborty, Subrataen
local.search.authorPradhan, Biswajeeten
local.uneassociationNoen
dc.date.presented2019-11-20-
local.atsiresearchNoen
local.sensitive.culturalNoen
local.year.available2020en
local.year.published2020en
local.year.presented2019en
local.fileurl.closedpublishedhttps://rune.une.edu.au/web/retrieve/1eefdabd-c472-407b-a451-b028c5f6704een
local.subject.for2020460102 Applications in healthen
local.subject.for2020461103 Deep learningen
local.subject.for2020460308 Pattern recognitionen
local.subject.seo2020209999 Other health not elsewhere classifieden
local.subject.seo2020280115 Expanding knowledge in the information and computing sciencesen
local.date.start2019-11-18-
local.date.end2019-11-22-
Appears in Collections:Conference Publication
School of Science and Technology
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